Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study by Chi Pui Pang, Weiqi Chen, Mingzhi Zhang, Tsz Kin Ng, Yi Zheng, Guihua Zhang, Jian-Wei Lin, Ji Wang, Jie Ji, Ling-Ping Cen, Peiwen Xie, Yongqun Xiong, Hanfu Wu, Dongjie Li

“…According to the UK DR screening guideline, a DL model based on colour retinal images with five-dimensional classifiers, namely image quality, retinopathy, maculopathy gradability, maculopathy and photocoagulation, was developed. Referable decisions were generated by integrating the output of all classifiers and reported at the image, eye and patient level. …”
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The Effect of Chewing Simulation on Flexural Strength of Different Lithium Disilicate Ceramics by Alsulimani O, Yousief SA, Al-Dabbagh RA, Attar EA, Bukhary DM, Algamaiah H, Musawa K, Subahi A, Abuzinadah SH, Alhaddad AJ, Alqahtani WMS, Emam ANM, Alqhtani MA, Elmarakby AM

“…Each primary group was further split into two subgroups (n=19) based on surface treatment: group E into (E0 & E1) and group L into (L0 & L1). …”
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Array Three-Dimensional SAR Imaging via Composite Low-Rank and Sparse Prior by Zhiliang Yang, Yangyang Wang, Chudi Zhang, Xu Zhan, Guohao Sun, Yuxuan Liu, Yuru Mao

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Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3 by Abhiram Sharma, R. Parvathi

“…The methodology involves rigorous data preprocessing, including normalization, augmentation, and dataset splitting, to ensure robust training and validation. …”
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PHYSICS-DRIVEN FEATURE CREATION TO IMPROVE MACHINE LEARNING MODELS PERFORMANCE FOR OIL PRODUCTION RATE PREDICTION by Eghbal Motaei, Seyed Mehdi Tabatabai, Tarek Ganat, Ahmad Khanifar, Sulaiman Dzaiy, Timur Chis

“…Several machine learning techniques, such as SVM, k-NN, Decision Tree, Random Forest, and linear regression, were constructed using PCA feature selection. …”
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Integrative analysis of anoikis-related prognostic signature to evaluate the immune landscape and predict therapeutic response in stomach adenocarcinoma by Ziyi Zhou, Lanlan Yang, Yuan Fang, Rongzhong Xu, Xi Wang, Yuli Wang, Zhihong Fang

“…The anoikis risk score (ARS) incorporated 7 genes and stratified patients into highand low-risk subgroups by median value splitting. In addition, external validation was performed based on GSE66229, GSE15459, and GSE84437 cohorts. …”
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The Bioethics-CSR Divide by Caio Caesar Dib

“…In the political arena, the end of the Cold War led to an impasse in the discourse concerning human rights,[15] which previously had been split between the defense of civil and political rights on one side and social rights on the other. …”
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Development and external validation of a dynamic nomogram for predicting the risk of functional outcome after 90 days in patients with acute intracerebral hemorrhage by Shaojie Li, Hongjian Li, Jiani Chen, Baofang Wu, Jiayin Wang, Chaocan Hong, Changhu Yan, Weizhi Qiu, Yasong Li, Hongzhi Gao

“…This study aimed to develop a practical nomogram for risk prediction of poor prognosis after 90 days in patients with intracerebral hemorrhage.MethodsA retrospective study was conducted on 638 patients with intracerebral hemorrhage in the Second Hospital of Fujian Medical University, China, who were divided into a training set (n = 446) and a test set (n = 192) by random splitting. Then the data on demographics, clinical symptoms, imaging characteristics, and laboratory findings were collected. …”
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A novel machine learning approach for spatiotemporal prediction of EMS events: A case study from Barranquilla, Colombia by Dionicio Neira-Rodado, Juan Camilo Paz-Roa, John Willmer Escobar, Miguel Ángel Ortiz-Barrios

“…Anticipating the timing and location of future emergency calls is crucial for making informed decisions about vehicle location and relocation, ultimately reducing response times and enhancing service quality. …”
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